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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Segmentation and Insights | 18% | - Calculated vs. streaming insights - Segmentation concepts and business scenarios - Segment creation, maintenance, and membership analysis |
| Topic 2: Data Ingestion and Modeling | 20% | - Ingestion from various source systems - Transformation and data mapping capabilities - Validation and inspection of ingested data - Data modeling best practices aligned with identity resolution |
| Topic 3: Act on Data | 18% | - Activation concepts and use cases - Attributes, related attributes, and timing dependencies - Troubleshooting activation issues - Data actions and requirements |
| Topic 4: Data Cloud Overview | 18% | - Architecture, dependencies, and lifecycle - Data ethics and responsible usage principles - Common enterprise use cases - Core functions, terminology, and business value |
| Topic 5: Identity Resolution | 14% | - Matching rules and application - Unified identity outcomes and use cases - Reconciliation rules and data unification |
| Topic 6: Data Cloud Setup and Administration | 12% | - Data exploration and diagnostics: Explorer tools, APIs - Data streams, data bundles, and data spaces - Permissions, permission sets, and org settings - Administration tools: reports, dashboards, flows, packaging |
>> New Data-Con-101 Exam Questions <<
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NEW QUESTION # 119
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
Answer: A
Explanation:
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
NEW QUESTION # 120
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers
Answer: A,B
Explanation:
The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer:
New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate.
Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.
Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
NEW QUESTION # 121
Which two steps should a consultant take if a successfully configured Amazon S3 data stream fails to refresh with a "NO FILE FOUND" error message?
Choose 2 answers
Answer: A,B
Explanation:
A "NO FILE FOUND" error message indicates that Data Cloud cannot access or locate the file from the Amazon S3 source. There are two possible reasons for this error and two corresponding steps that a consultant should take to troubleshoot it:
The Data Cloud user does not have the correct permissions to read the file from the Amazon S3 bucket. This could happen if the user's permission set or profile does not include the Data Cloud Data Stream Read permission, or if the user's Amazon S3 credentials are invalid or expired. To fix this issue, the consultant should check and update the user's permissions and credentials in Data Cloud and Amazon S3, respectively.
The file does not exist in the specified bucket location. This could happen if the file name or path has changed, or if the file has been deleted or moved from the Amazon S3 bucket. To fix this issue, the consultant should check and verify the file name and path in the Amazon S3 bucket, and update the data stream configuration in Data Cloud accordingly. References: Create Amazon S3 Data Stream in Data Cloud, How to Use the Amazon S3 Storage Connector in Data Cloud, Amazon S3 Connection
NEW QUESTION # 122
A new user of Data Cloud only needs to be able to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user will also need to make changes if required.
What is the minimum permission set needed to accommodate this use case?
Answer: A
Explanation:
The Data Cloud User permission set is the minimum permission set needed to accommodate this use case.
The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. References: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit
NEW QUESTION # 123
A consultant is setting up Data Cloud for a multi-brand organization and is using data spaces to segregate its data for various brands.
While starting the mapping of a data stream, the consultant notices that they cannot map the object for one of the brands.
What should the consultant do to make the object available for a new data space?
Answer: A
Explanation:
When setting up Data Cloud for a multi-brand organization, if a consultant cannot map an object for one of the brands during data stream setup, they should navigate to the Data Space tab and select the object to include it in the new data space. Here's why:
Understanding the Issue
The consultant is using data spaces to segregate data for different brands.
While mapping a data stream, they notice that an object is unavailable for one of the brands.
This indicates that the object has not been associated with the new data space.
Why Navigate to the Data Space Tab?
Data Spaces and Object Availability :
Objects must be explicitly added to a data space before they can be used in mappings or transformations within that space.
If an object is missing, it means it has not been included in the data space configuration.
Solution Approach :
By navigating to the Data Space tab , the consultant can add the required object to the new data space.
This ensures the object becomes available for mapping and use in the data stream.
Steps to Resolve the Issue
Step 1: Navigate to the Data Space Tab
Go to Data Cloud > Data Spaces and locate the new data space for the brand.
Step 2: Add the Missing Object
Select the data space and click on Edit .
Add the required object (e.g., a Data Model Object or Data Lake Object) to the data space.
Step 3: Save and Verify
Save the changes and return to the data stream setup.
Verify that the object is now available for mapping.
Step 4: Complete the Mapping
Proceed with mapping the object in the data stream.
Why Not Other Options?
A). Create a new data stream and map the second data stream to the data space :Creating a new data stream is unnecessary if the issue is simply object availability in the data space.
B). Copy data from the default data space to a new DMO using the Data Copy feature and link this DMO to the new data space :This is overly complex and not required if the object can simply be added to the data space.
C). Create a batch transform to split data between different data spaces :Batch transforms are used for data processing, not for resolving object availability issues.
Conclusion
The correct solution is to navigate to the Data Space tab and select the object to include it in the new data space . This ensures the object is available for mapping and resolves the issue efficiently.
NEW QUESTION # 124
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